Artificial Intelligence Specialist

AI Deployment Lead / Instructor – Devin AI

Charlotte, NC / Dallas, TX / Chicago, IL / New York, NY

Demonstrated experience training, mentoring, or enabling engineering teams on new tools or workflows — prior instructor, enablement, or forward-deployed engineering experience strongly preferred

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We are seeking a highly skilled AI Deployment Lead – Devin AI with deep expertise in Devin and modern Generative AI (GenAI) tools to support enterprise-scale rollout and adoption across Line of Business (LOB) engineering team

s.This is a hands-on engineering role focused on enabling LOB teams to improve their product delivery lifecycle through effective utilization of GenAI tools, coupled with a strong ability to train and upskill engineering teams on autonomous development workflows. The ideal candidate combines solid software engineering fundamentals, practical experience integrating GenAI solutions into enterprise development environments, and demonstrated success teaching others to be effective with these tools — not just executing tasks independentl

y.This role requires close partnership with product, platform, security, and engineering teams to accelerate delivery, improve developer productivity, and drive scalable, well-governed adoption of GenAI capabilities across the organizatio

n.Responsibiliti

• esLead the end-to-end rollout and scaling of GenAI tools (Devin, Claude Code, Cursor) across CDXO and LOB engineering team
• s.Act as a hands-on engineer, building and integrating solutions into enterprise SDLC workflows (CI/CD pipelines, repositories, APIs
• ).Define and execute enterprise-wide rollout strategies, including phased onboarding and scaling model
• s.Partner with LOB teams to enhance the product delivery lifecycle using GenAI capabilitie
• s.Design and deliver structured developer onboarding, training, and enablement programs — teaching engineering teams to work effectively with autonomous development tools, not simply completing tasks on their behal
• f.Advise teams on when to apply autonomous (Devin) vs. assistive (Copilot) approaches based on use case and risk profil
• e.Monitor tool adoption, usage metrics, and performance, ensuring continuous optimizatio
• n.Provide hands-on troubleshooting, performance tuning, and scaling suppor
• t.Establish reusable playbooks and best practices for enterprise-wide GenAI adoptio
• n.Ensure alignment with enterprise governance, security, and compliance frameworks, including secrets/identity management practices for agent-based toolin
• g.Identify adoption gaps and proactively drive improvements in efficiency and scalabilit

y.Requirement

• s:5–8+ years of software engineering experience, with strong fundamentals in at least one enterprise stack (e.g., Java, Python, or TypeScript/React/Angular
• ).Working knowledge of distributed systems, microservices, event-driven architectures, and API design/integratio
• n.Hands-on experience with CI/CD pipelines and developer tooling ecosystem
• s.Familiarity with cloud platforms such as OpenShift (OCP) and Google Cloud Platform (GCP
• ).Demonstrated experience training, mentoring, or enabling engineering teams on new tools or workflows — prior instructor, enablement, or forward-deployed engineering experience strongly preferre

d.
GenAI / LLM Expert

iseHands-on experience wi

• th:De
• vinClaude / Anthropic mod
• elsCursor or similar developer productivity tools (Copilot, et

c.)
Strong understanding

• of:Prompt enginee
• ringRAG (Retrieval Augmented Generat
• ion)Agent-based workflows and tool u
• sageMulti-agent architect
• uresMCP (Model Context Protocol) servers and integrat
• ionsAgentic systems including orchestration, tool chaining, and autonomous decision-driven workf